Sentiment Analysis and Classification on Amazon Products using Improved Support Vector Machine for Multiclass Classification

There is a huge increase in number of peoples who have been accessing many social networking sites especially user post or reviews for a specific product, company, brand, individual, forums and movies etc. These reviews are helpful in judging customer perception on certain thing. The development of algorithms that could automate the categorization of distinct comments based on feedback from consumers became an analyst project, and this automated classification process is known as sentiment analysis. This research main goal is to analyze Amazon product reviews using an approach to Machine Learning (ML) built around TF-IDF and then employ the Support Vector Machine (SVM) algorithm to categorize the sentiment scores and sentences. SVM can handle binomial classification but the customer reviews is mostly classified into positive, negative and neutral and in some applications, it is fine grained into star ratings such 1-5 or sometimes 1-10. Also, in some applications features or attributes are high in number in which some are irrelevant. Hence, this work applies feature subset algorithm and improves the existing SVM to handle multiclass classification. The Sentiment analysis, Rapidminer tool is considered for classification and the results are visualized, assessed with suitable classification metrics

A correlation of clinical, hormonal and ultrasonography features of polycystic ovarian syndrome among adolescent and reproductive age group women attending OPD in Navodaya medical college

Background: Polycystic ovarian syndrome is the most common complex endocrine disorder in women of reproductive age. It is characterized by an array of clinical, endocrinal and metabolic manifestation. Aim of this study was to examine the correlation between clinical, hormonal and ultrasonography features in women diagnosed as polycystic ovarian syndrome. Methods: A cross sectional study of 100 reproductive age group women who had irregular cycles and polycystic ovarian morphology on ultrasound. Data about the menstrual history and anthropometric measurements were collected. Clinical observations were like hirsuitism and acanthosis nigricans was noted. Results: In all 100 PCOS women were studied and analysed. The mean age was 24.27(±5.64), mean BMI was 26(±4.8). Among the PCOS women 82% had oligo menorrhoea, 38% had hirsuitism and LH:FSH ratio deranged in 37% cases. The association between women having oligomenorrhoea and obesity with PCO morphology on scan was statistically significant. Conclusions: Young women who are diagnosed as dysregulated PCO are at a high risk to develop PCOD and long term sequel such as diabetes, hypertension and infertility. Lifestyle modification is advisable for managing symptoms and preventing long term complications and have a quality life

Application of Linear Discriminant Analysis in Dimensionality Reduction for Hand Motion Classification

The classification of upper-limb movements based on surface electromyography (EMG) signals is an important issue in the control of assistive devices and rehabilitation systems. Increasing the number of EMG channels and features in order to increase the number of control commands can yield a high dimensional feature vector. To cope with the accuracy and computation problems associated with high dimensionality, it is commonplace to apply a processing step that transforms the data to a space of significantly lower dimensions with only a limited loss of useful information. Linear discriminant analysis (LDA) has been successfully applied as an EMG feature projection method. Recently, a number of extended LDA-based algorithms have been proposed, which are more competitive in terms of both classification accuracy and computational costs/times with classical LDA. This paper presents the findings of a comparative study of classical LDA and five extended LDA methods. From a quantitative comparison based on seven multi-feature sets, three extended LDA-based algorithms, consisting of uncorrelated LDA, orthogonal LDA and orthogonal fuzzy neighborhood discriminant analysis, produce better class separability when compared with a baseline system (without feature projection), principle component analysis (PCA), and classical LDA. Based on a 7-dimension time domain and time-scale feature vectors, these methods achieved respectively 95.2% and 93.2% classification accuracy by using a linear discriminant classifier

Influence of different types of soils on the growth and yield of Quinoa (Chenopodium quinoa Wild.)

Quinoa is a resilient high-yielding pseudo cereal, gaining attention because of its high nutritional value, strong growth potential, and tremendous source of essential amino acids, micronutrients, vitamins, phenolic compounds, and minerals. The main aim of this investigation was to find the best suitable soil type for maximizing the growth and yield of Quinoa. The pot study was undertaken at the Department of Agronomy, Tamil Nadu Agricultural University, Coimbatore, during the Kharif 2022 season. Eight soil samples (clay loam soils of wetlands of TNAU, sandy loam soils of eastern block of TNAU, sandy loam soils of Mettupalayam, sandy clay loam soils of 36 B eastern block of TNAU, sandy clay loam soils of 37 B eastern block of TNAU, clay loam soils of Ooty, sandy clay loam soils of Govindanaickenpalayam and sandy clay loam soils of Annur) were collected round Coimbatore in Tamil Nadu and tested in a complete randomized design with three replications. The pot study results revealed that growth parameters viz. Plant height (81.5 cm), number of leaves plant-1 (164.8), leaf area (317.7 cm2), number of branches plant-1 (38.0) and dry matter production (22.78 g) were significantly higher in the clay loam soils of Ooty than all other soil types. Similarly, yield attributes such as the number of panicles plant-1 (21.7), panicle length (13.08 cm), number of grains panicle-1 (3050) and grain yield plant-1 (9.60 g) of Quinoa were also higher in the same clay loam soils followed by that in sandy clay loam soils of Govindanaickenpalayam. Red soils of Mettupalayam had shown the lowest growth, yield and yield attributes of Quinoa. Based on the above results, it was concluded that the clay loam soil of Ooty was the best suited for cultivating Quinoa crops

Effect of hydrogen bonding and solvent polarity on the fluorescence quenching and dipole moment of 2-methoxypyridin-3-yl-3-boronic acid

Two photophysical properties namely, fluorescence quenching and dipole moment (both ground state and excited state) of 2-methoxypyridin-3-yl-3-boronic acid (2MPBA) have been investigated in alcohol environment using steady state fluorescence technique at 300 K. In quenching studies, a rare but not unusual observation; negative Stern-Volmer (S-V) deviation has been noticed. It has been explained using the concept of solute’s conformational changes in the ground state due to inter-molecular and intra-molecular hydrogen bonding in alcohol environment. The spectroscopic data has been processed using Lehrer equation and thereby Stern-Volmer constant (KSV) has been evaluated. It has been found to be above 100 for most of the solvents used. The data related to dipole moment has been examined using different solvent polarity functions. Theoretical calculation of dipole moment in the ground state has been done using Gaussian software. The general solute–solvent interactions and hydrogen bond interactions have been found to be operative. An appreciable red shift of about 25 nm in the emission spectra has been identified with the rise in solvent polarity and decrease in molar mass of alcohols. It confirms the π→π* transition as well as the possibility of intra-molecular charge transfer (ICT) character in the emitting singlet state of 2MPBA

Wifi Infrastructure Security System from Vulnerable Attacks

Abstract Wi-Fi is a very popular wireless technology which is powerful core for the global digital infrastructure. A device connected using Wi-Fi can access the network resource such as the Internet via a wireless network access point. Recent discoveries and initiatives highlight a simple fact that the core is just as vulnerable as the edge. Wi-Fi can be less secure than wired connections because an intruder does not need a physical connection. Though security threats are imminent due to the open nature of communication, there are certain ways to protect the infrastructure of a network.In this paper, we examine the vulnerabilities of Wi-Fi network and this includes the intrusion detection in the security architecture of that network. We have shown such mechanism to solve arrival of intruders by Man-in -the-middle attack on a Wi-Fi network. Also, provide the steps to eliminate hackers from the Wi-Fi network and descriptions regarding the operations performed by different tools to avoid attackers from network. There are several holes in the wireless environment through which the attacks enter the network. In future those holes may be blocked completely by eliminating hackers from all attacks through which they enter. We also discuss a number of available solutions for controlling those threats

Revolutionizing Crop Production: The Imperative of Speed Breeding Technology in Modern Crop Improvement

Speed breeding (SB) technology is an innovative solution to shorten the breeding cycle and accelerate crop improvement. The key factors of plant growth and development, including photoperiod, light intensity and quality, temperature, relative humidity, planting density and plant nutrition are manipulated in such a way as to stimulate flowering and seed set under controlled conditions. The development of SB technology may be challenging as crops tend to vary in their response to physiological manipulations. Therefore, crop-specific optimization is highly critical to developing successful SB technology in crops. The SB technology can also be synergistically integrated with cutting edge genomics and marker-assisted selection technologies to enhance genetic gain in crop breeding programmes. In this review, various aspects concerning the science and techniques underpinning SB technology, the successful implementation of SB technology in different crops, the inherent challenges faced, and the potential opportunities to integrate SB technology with cutting-edge genomics technologies towards accelerating crop improvement are discussed

Thyroid pathology in canine parvoviral infection

The hypothalamic-pituitary-thyroid axis is suppressed by pro-inflammatory mediators in systemic disease, which affects the thyroid hormone level. Canine parvovirus is one of the important infectious diseases which causes profound morbidity as well as mortality in dogs. It is found that canine parvovirus infection can result in non-thyroidal sickness syndrome. The relation between thyroid pathology and canine parvovirus infection will pave the way for therapeutic and preventive measures for this infectious disease. This study was conducted on 61 dog carcasses brought to the Department of Veterinary Pathology, College of Veterinary and Animal Sciences, Pookode during one year period. Among 61 cases, nine were found to be positive for canine parvovirus which constitutes an incidence of 14.75 per cent. Analysis of gross and histopathological lesions in canine parvovirus positive cases was the goal of this investigation. The gross lesions observed were paleness and nodular growth and histopathological lesions encountered were lymphocytic thyroiditis, colloidal goiter, c cell hyperplasia, severe fibrotic changes and neoplastic lesions. Further research is required to understand the pathophysiology of the euthyroid sick syndrome in canine parvoviral infection

Distance simulation in the health professions: a scoping review

Background Distance simulation is defined as simulation experiences in which participants and/or facilitators are separated from each other by geographic distance and/or time. The use of distance simulation as an education technique expanded rapidly with the recent COVID-19 pandemic, with a concomitant increase in scholarly work. Methods A scoping review was performed to review and characterize the distance simulation literature. With the assistance of an informationist, the literature was systematically searched. Each abstract was reviewed by two researchers and disagreements were addressed by consensus. Risk of bias of the included studies was evaluated using the Risk of Bias 2 (RoB 2) and Risk of Bias in Non-randomized Studies of Interventions (ROBINS-I) tools. Results Six thousand nine hundred sixty-nine abstracts were screened, ultimately leading to 124 papers in the final dataset for extraction. A variety of simulation modalities, contexts, and distance simulation technologies were identified, with activities covering a range of content areas. Only 72 papers presented outcomes and sufficient detail to be analyzed for risk of bias. Most studies had moderate to high risk of bias, most commonly related to confounding factors, intervention classification, or measurement of outcomes. Conclusions Most of the papers reviewed during the more than 20-year time period captured in this study presented early work or low-level outcomes. More standardization around reporting is needed to facilitate a clear and shared understanding of future distance simulation research. As the broader simulation community gains more experience with distance simulation, more studies are needed to inform when and how it should be used

IndEcho study: Cohort study investigating birth size, childhood growth and young adult cardiovascular risk factors as predictors of midlife myocardial structure and function in South Asians

Introduction South Asians have high rates of cardiovascular disease (CVD) and its risk factors (hypertension, diabetes, dyslipidaemia and central obesity). Left ventricular (LV) hypertrophy and dysfunction are features of these disorders and important predictors of CVD mortality. Lower birth and infant weight and greater childhood weight gain are associated with increased adult CVD mortality, but there are few data on their relationship to LV function. The IndEcho study will examine associations of birth size, growth during infancy, childhood and adolescence and CVD risk factors in young adulthood with midlife cardiac structure and function in South Asian Indians. Methods and analysis We propose to study approximately 3000 men and women aged 43–50 years from two birth cohorts established in 1969–1973: the New Delhi Birth Cohort (n=1508) and Vellore Birth Cohort (n=2156). They had serial measurements of weight and height from birth to early adulthood. CVD risk markers (body composition, blood pressure, glucose tolerance and lipids) and lifestyle characteristics (tobacco and alcohol consumption, physical activity, socioeconomic status) were assessed at age ~30 years. Clinical measurements in IndEcho will include anthropometry, blood pressure, biochemistry (glucose, fasting insulin and lipids, urinary albumin/creatinine ratio) and body composition by dual energy X-ray absorptiometry and bioelectrical impedance. Outcomes are LV mass and indices of LV systolic and diastolic function assessed by two-dimensional and Doppler echocardiography, carotid intimal-media thickness and ECG indicators of ischaemia. Regression and conditional growth models, adjusted for potential confounders, will be used to study associations of childhood and young adult exposures with these cardiovascular outcomes. Ethics and dissemination The study has been approved by the Health Ministry Steering Committee, Government of India and institutional ethics committees of participating centres in India and the University of Southampton, UK. Results will be disseminated through scientific meetings and peer-reviewed journals